3D Data Acquisition and Registration using Two Opposing Kinects

Vahid Soleimani, Majid Mirmehdi, Dima Aldamen, Sion Hannuna, Massimo Camplani

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

6 Citations (Scopus)
476 Downloads (Pure)

Abstract

We present an automatic, open source data acquisition and calibration approach using two opposing RGBD sensors (Kinect V2) and demonstrate its efficacy for dynamic object reconstruction in the context of monitoring for remote lung function assessment. First, the relative pose of the two RGBD sensors is estimated through a calibration stage and rigid transformation parameters are computed.
These are then used to align and register point clouds obtained from the sensors at frame level. We validated the proposed system by performing experiments on known-size box objects with the results demonstrating accurate measurements. We also report on dynamic object reconstruction by way of human subjects undergoing respiratory functional assessment.
Original languageEnglish
Title of host publication2016 International Conference on 3D Vision (3DV 2016)
Subtitle of host publicationConference Proceeding 25-28 October 2016, Stanford, CA, USA
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages128-137
Number of pages10
ISBN (Electronic)9781509054084
ISBN (Print)9781509054077
DOIs
Publication statusPublished - 28 Oct 2016
Event2016 International Conference on 3D Vision - University of Stanford, California, United States
Duration: 25 Oct 201628 Oct 2016
http://3dv.stanford.edu/index.html

Conference

Conference2016 International Conference on 3D Vision
Abbreviated title3D Vision 2016
CountryUnited States
CityCalifornia
Period25/10/1628/10/16
Internet address

Structured keywords

  • Digital Health

Keywords

  • Digital Health

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